Adaptive Beam Pruning for Speech Recognition
Limin Du · Audio Engineering · 2004
In large vocabulary continuous speech recognition, huge spaces are searched during the recognition process, resulting in vast computational cost. While most pruning search strategies can reduce the computation, the recognition rate often decreases. Based on adaptive control theory,a novel pruning method that can automatically steer beam width to make search space attain a predefined size is presented. Average active phone-model-instance as the dynamic reference signal of the adaptive system is farther used. Compared with the base system which is integrated with fixed beam pruning and MAPMI pruning, the proposed method leads to a significant reduction in computing time and a slightly improvement in word accuracy. By measuring the RTF, this system is proved to have good real-time performances.